Epoch: 0001 train_loss= 2.11411 train_acc= 0.09164 val_loss= 2.10621 val_acc= 0.03448 time= 0.29738
Epoch: 0002 train_loss= 2.10453 train_acc= 0.10512 val_loss= 2.10395 val_acc= 0.03448 time= 0.00000
Epoch: 0003 train_loss= 2.09005 train_acc= 0.10512 val_loss= 2.10258 val_acc= 0.10345 time= 0.01515
Epoch: 0004 train_loss= 2.09054 train_acc= 0.11051 val_loss= 2.10111 val_acc= 0.06897 time= 0.00000
Epoch: 0005 train_loss= 2.08837 train_acc= 0.10782 val_loss= 2.10059 val_acc= 0.10345 time= 0.01562
Epoch: 0006 train_loss= 2.08565 train_acc= 0.14016 val_loss= 2.10038 val_acc= 0.20690 time= 0.01563
Epoch: 0007 train_loss= 2.07901 train_acc= 0.14286 val_loss= 2.10049 val_acc= 0.20690 time= 0.00000
Epoch: 0008 train_loss= 2.08300 train_acc= 0.14555 val_loss= 2.10051 val_acc= 0.20690 time= 0.01563
Epoch: 0009 train_loss= 2.07822 train_acc= 0.15633 val_loss= 2.10062 val_acc= 0.20690 time= 0.00000
Epoch: 0010 train_loss= 2.07552 train_acc= 0.15364 val_loss= 2.10045 val_acc= 0.20690 time= 0.01563
Epoch: 0011 train_loss= 2.07603 train_acc= 0.15094 val_loss= 2.10032 val_acc= 0.17241 time= 0.00000
Epoch: 0012 train_loss= 2.07458 train_acc= 0.16981 val_loss= 2.10014 val_acc= 0.17241 time= 0.01563
Epoch: 0013 train_loss= 2.08178 train_acc= 0.12938 val_loss= 2.09987 val_acc= 0.17241 time= 0.01563
Epoch: 0014 train_loss= 2.07637 train_acc= 0.15364 val_loss= 2.09884 val_acc= 0.17241 time= 0.00000
Epoch: 0015 train_loss= 2.07180 train_acc= 0.14825 val_loss= 2.09806 val_acc= 0.17241 time= 0.01562
Epoch: 0016 train_loss= 2.06904 train_acc= 0.16442 val_loss= 2.09746 val_acc= 0.17241 time= 0.00000
Epoch: 0017 train_loss= 2.07290 train_acc= 0.15094 val_loss= 2.09702 val_acc= 0.17241 time= 0.01563
Epoch: 0018 train_loss= 2.06995 train_acc= 0.15633 val_loss= 2.09665 val_acc= 0.17241 time= 0.00000
Epoch: 0019 train_loss= 2.06938 train_acc= 0.16712 val_loss= 2.09601 val_acc= 0.17241 time= 0.01563
Epoch: 0020 train_loss= 2.06778 train_acc= 0.14555 val_loss= 2.09541 val_acc= 0.20690 time= 0.01563
Epoch: 0021 train_loss= 2.07171 train_acc= 0.16712 val_loss= 2.09474 val_acc= 0.20690 time= 0.00000
Epoch: 0022 train_loss= 2.06637 train_acc= 0.15364 val_loss= 2.09425 val_acc= 0.13793 time= 0.01562
Epoch: 0023 train_loss= 2.07123 train_acc= 0.15364 val_loss= 2.09263 val_acc= 0.13793 time= 0.00000
Epoch: 0024 train_loss= 2.06813 train_acc= 0.15903 val_loss= 2.09058 val_acc= 0.13793 time= 0.01563
Epoch: 0025 train_loss= 2.06704 train_acc= 0.15903 val_loss= 2.08861 val_acc= 0.13793 time= 0.01563
Epoch: 0026 train_loss= 2.06596 train_acc= 0.16442 val_loss= 2.08716 val_acc= 0.06897 time= 0.00000
Epoch: 0027 train_loss= 2.06543 train_acc= 0.16712 val_loss= 2.08574 val_acc= 0.06897 time= 0.01563
Epoch: 0028 train_loss= 2.06473 train_acc= 0.16173 val_loss= 2.08400 val_acc= 0.10345 time= 0.00000
Epoch: 0029 train_loss= 2.06542 train_acc= 0.14825 val_loss= 2.08226 val_acc= 0.20690 time= 0.01563
Epoch: 0030 train_loss= 2.06649 train_acc= 0.13747 val_loss= 2.08032 val_acc= 0.20690 time= 0.00000
Epoch: 0031 train_loss= 2.06129 train_acc= 0.15364 val_loss= 2.07815 val_acc= 0.20690 time= 0.01563
Epoch: 0032 train_loss= 2.06393 train_acc= 0.14825 val_loss= 2.07688 val_acc= 0.20690 time= 0.01563
Epoch: 0033 train_loss= 2.06714 train_acc= 0.15364 val_loss= 2.07553 val_acc= 0.20690 time= 0.00000
Epoch: 0034 train_loss= 2.06433 train_acc= 0.15633 val_loss= 2.07477 val_acc= 0.17241 time= 0.01563
Epoch: 0035 train_loss= 2.06013 train_acc= 0.15094 val_loss= 2.07441 val_acc= 0.13793 time= 0.00000
Epoch: 0036 train_loss= 2.06360 train_acc= 0.17790 val_loss= 2.07443 val_acc= 0.10345 time= 0.01563
Epoch: 0037 train_loss= 2.06479 train_acc= 0.15364 val_loss= 2.07510 val_acc= 0.06897 time= 0.01563
Epoch: 0038 train_loss= 2.06302 train_acc= 0.16981 val_loss= 2.07553 val_acc= 0.06897 time= 0.00000
Epoch: 0039 train_loss= 2.06077 train_acc= 0.19137 val_loss= 2.07597 val_acc= 0.10345 time= 0.01563
Epoch: 0040 train_loss= 2.05940 train_acc= 0.18329 val_loss= 2.07668 val_acc= 0.10345 time= 0.00000
Early stopping...
Optimization Finished!
Test set results: cost= 2.05154 accuracy= 0.18644 time= 0.00000 
